A consistent method of estimation for the parameters of the three-parameter inverse Gaussian distribution

被引：5
|
作者：
Nagatsuka, Hideki [1 ]
Balakrishnan, N. [2 ]
机构：
[1] Tokyo Metropolitan Univ, Fac Syst Design, Hino, Tokyo 1910065, Japan
[2] McMaster Univ, Dept Math & Stat, Hamilton, ON L8S 4K1, Canada
来源：
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION | 2013年 / 83卷 / 10期
关键词：
maximum likelihood method; mixed moments method; conditional method of moments; order statistics; threshold parameter; consistency; MODIFIED MOMENT ESTIMATION; MAXIMUM-LIKELIHOOD; STATISTICAL PROPERTIES;
D O I：
10.1080/00949655.2012.674130
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In this paper, we propose a consistent method of estimation for the parameters of the three-parameter inverse Gaussian distribution. We then discuss some properties of these estimators and show by means of a Monte Carlo simulation study that the proposed estimators perform better than some other prominent estimators in terms of bias and root mean squared error. Finally, we present two real-life examples to illustrate the method of inference developed here.
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页码：1915 / 1931
页数：17
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